{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "Pipelines: Testing Methods to Reduce Dimensionality"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'classify': SVC(C=10, cache_size=200, class_weight=None, coef0=0.0,\n",
       "   decision_function_shape='ovr', degree=3, gamma='auto', kernel='rbf',\n",
       "   max_iter=-1, probability=False, random_state=None, shrinking=True,\n",
       "   tol=0.001, verbose=False),\n",
       " 'classify__C': 10,\n",
       " 'reduce_dim': PCA(copy=True, iterated_power='auto', n_components=3, random_state=None,\n",
       "   svd_solver='auto', tol=0.0, whiten=False),\n",
       " 'reduce_dim__n_components': 3}"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.datasets import load_iris\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "from sklearn.pipeline import Pipeline\n",
    "from sklearn.svm import SVC, LinearSVC\n",
    "from sklearn.decomposition import PCA, NMF, TruncatedSVD\n",
    "from sklearn.manifold import Isomap\n",
    "%matplotlib inline\n",
    "\n",
    "\n",
    "pipe = Pipeline([\n",
    "    ('reduce_dim', PCA()),\n",
    "    ('classify', SVC())\n",
    "])\n",
    "\n",
    "\n",
    "\n",
    "param_grid = [\n",
    "    {\n",
    "        'reduce_dim': [PCA(), NMF(),Isomap(),TruncatedSVD()],\n",
    "        'reduce_dim__n_components': [2, 3],\n",
    "        'classify' : [SVC(), LinearSVC()],\n",
    "        'classify__C': [1, 10, 100, 1000]\n",
    "    },\n",
    "]\n",
    "\n",
    "\n",
    "\n",
    "grid = GridSearchCV(pipe, cv=3, n_jobs=-1, param_grid=param_grid)\n",
    "iris = load_iris()\n",
    "grid.fit(iris.data, iris.target)\n",
    "grid.best_params_\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.97999999999999998"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grid.best_score_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mean_fit_time</th>\n",
       "      <th>mean_score_time</th>\n",
       "      <th>mean_test_score</th>\n",
       "      <th>mean_train_score</th>\n",
       "      <th>param_classify</th>\n",
       "      <th>param_classify__C</th>\n",
       "      <th>param_reduce_dim</th>\n",
       "      <th>param_reduce_dim__n_components</th>\n",
       "      <th>params</th>\n",
       "      <th>rank_test_score</th>\n",
       "      <th>split0_test_score</th>\n",
       "      <th>split0_train_score</th>\n",
       "      <th>split1_test_score</th>\n",
       "      <th>split1_train_score</th>\n",
       "      <th>split2_test_score</th>\n",
       "      <th>split2_train_score</th>\n",
       "      <th>std_fit_time</th>\n",
       "      <th>std_score_time</th>\n",
       "      <th>std_test_score</th>\n",
       "      <th>std_train_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.181333</td>\n",
       "      <td>0.002000</td>\n",
       "      <td>0.966667</td>\n",
       "      <td>0.963458</td>\n",
       "      <td>SVC(C=10, cache_size=200, class_weight=None, c...</td>\n",
       "      <td>1</td>\n",
       "      <td>PCA(copy=True, iterated_power='auto', n_compon...</td>\n",
       "      <td>2</td>\n",
       "      <td>{u'classify__C': 1, u'reduce_dim': PCA(copy=Tr...</td>\n",
       "      <td>11</td>\n",
       "      <td>0.980392</td>\n",
       "      <td>0.959596</td>\n",
       "      <td>0.941176</td>\n",
       "      <td>0.979798</td>\n",
       "      <td>0.979167</td>\n",
       "      <td>0.950980</td>\n",
       "      <td>0.834724</td>\n",
       "      <td>1.123916e-07</td>\n",
       "      <td>0.018302</td>\n",
       "      <td>0.012078</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.030000</td>\n",
       "      <td>0.001000</td>\n",
       "      <td>0.973333</td>\n",
       "      <td>0.983363</td>\n",
       "      <td>SVC(C=10, cache_size=200, class_weight=None, c...</td>\n",
       "      <td>1</td>\n",
       "      <td>PCA(copy=True, iterated_power='auto', n_compon...</td>\n",
       "      <td>3</td>\n",
       "      <td>{u'classify__C': 1, u'reduce_dim': PCA(copy=Tr...</td>\n",
       "      <td>3</td>\n",
       "      <td>0.980392</td>\n",
       "      <td>0.969697</td>\n",
       "      <td>0.960784</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.979167</td>\n",
       "      <td>0.980392</td>\n",
       "      <td>0.019131</td>\n",
       "      <td>1.123916e-07</td>\n",
       "      <td>0.009021</td>\n",
       "      <td>0.012548</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.111333</td>\n",
       "      <td>0.003000</td>\n",
       "      <td>0.973333</td>\n",
       "      <td>0.976728</td>\n",
       "      <td>SVC(C=10, cache_size=200, class_weight=None, c...</td>\n",
       "      <td>1</td>\n",
       "      <td>NMF(alpha=0.0, beta_loss='frobenius', init=Non...</td>\n",
       "      <td>2</td>\n",
       "      <td>{u'classify__C': 1, u'reduce_dim': NMF(alpha=0...</td>\n",
       "      <td>3</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.969697</td>\n",
       "      <td>0.941176</td>\n",
       "      <td>0.989899</td>\n",
       "      <td>0.979167</td>\n",
       "      <td>0.970588</td>\n",
       "      <td>0.024998</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.024581</td>\n",
       "      <td>0.009320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.202000</td>\n",
       "      <td>0.002000</td>\n",
       "      <td>0.900000</td>\n",
       "      <td>0.913547</td>\n",
       "      <td>SVC(C=10, cache_size=200, class_weight=None, c...</td>\n",
       "      <td>1</td>\n",
       "      <td>NMF(alpha=0.0, beta_loss='frobenius', init=Non...</td>\n",
       "      <td>3</td>\n",
       "      <td>{u'classify__C': 1, u'reduce_dim': NMF(alpha=0...</td>\n",
       "      <td>60</td>\n",
       "      <td>0.960784</td>\n",
       "      <td>0.888889</td>\n",
       "      <td>0.901961</td>\n",
       "      <td>0.959596</td>\n",
       "      <td>0.833333</td>\n",
       "      <td>0.892157</td>\n",
       "      <td>0.073544</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.051766</td>\n",
       "      <td>0.032589</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.189000</td>\n",
       "      <td>0.009000</td>\n",
       "      <td>0.933333</td>\n",
       "      <td>0.943454</td>\n",
       "      <td>SVC(C=10, cache_size=200, class_weight=None, c...</td>\n",
       "      <td>1</td>\n",
       "      <td>Isomap(eigen_solver='auto', max_iter=None, n_c...</td>\n",
       "      <td>2</td>\n",
       "      <td>{u'classify__C': 1, u'reduce_dim': Isomap(eige...</td>\n",
       "      <td>48</td>\n",
       "      <td>0.941176</td>\n",
       "      <td>0.919192</td>\n",
       "      <td>0.921569</td>\n",
       "      <td>0.979798</td>\n",
       "      <td>0.937500</td>\n",
       "      <td>0.931373</td>\n",
       "      <td>0.082426</td>\n",
       "      <td>4.320365e-03</td>\n",
       "      <td>0.008575</td>\n",
       "      <td>0.026176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.043333</td>\n",
       "      <td>0.011333</td>\n",
       "      <td>0.940000</td>\n",
       "      <td>0.950386</td>\n",
       "      <td>SVC(C=10, cache_size=200, class_weight=None, c...</td>\n",
       "      <td>1</td>\n",
       "      <td>Isomap(eigen_solver='auto', max_iter=None, n_c...</td>\n",
       "      <td>3</td>\n",
       "      <td>{u'classify__C': 1, u'reduce_dim': Isomap(eige...</td>\n",
       "      <td>45</td>\n",
       "      <td>0.960784</td>\n",
       "      <td>0.949495</td>\n",
       "      <td>0.921569</td>\n",
       "      <td>0.989899</td>\n",
       "      <td>0.937500</td>\n",
       "      <td>0.911765</td>\n",
       "      <td>0.005185</td>\n",
       "      <td>7.586547e-03</td>\n",
       "      <td>0.016260</td>\n",
       "      <td>0.031904</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.030000</td>\n",
       "      <td>0.001000</td>\n",
       "      <td>0.966667</td>\n",
       "      <td>0.966726</td>\n",
       "      <td>SVC(C=10, cache_size=200, class_weight=None, c...</td>\n",
       "      <td>1</td>\n",
       "      <td>TruncatedSVD(algorithm='randomized', n_compone...</td>\n",
       "      <td>2</td>\n",
       "      <td>{u'classify__C': 1, u'reduce_dim': TruncatedSV...</td>\n",
       "      <td>11</td>\n",
       "      <td>0.980392</td>\n",
       "      <td>0.959596</td>\n",
       "      <td>0.941176</td>\n",
       "      <td>0.979798</td>\n",
       "      <td>0.979167</td>\n",
       "      <td>0.960784</td>\n",
       "      <td>0.033297</td>\n",
       "      <td>8.164374e-04</td>\n",
       "      <td>0.018302</td>\n",
       "      <td>0.009256</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.003333</td>\n",
       "      <td>0.000667</td>\n",
       "      <td>0.973333</td>\n",
       "      <td>0.983363</td>\n",
       "      <td>SVC(C=10, cache_size=200, class_weight=None, c...</td>\n",
       "      <td>1</td>\n",
       "      <td>TruncatedSVD(algorithm='randomized', n_compone...</td>\n",
       "      <td>3</td>\n",
       "      <td>{u'classify__C': 1, u'reduce_dim': TruncatedSV...</td>\n",
       "      <td>3</td>\n",
       "      <td>0.980392</td>\n",
       "      <td>0.969697</td>\n",
       "      <td>0.960784</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.979167</td>\n",
       "      <td>0.980392</td>\n",
       "      <td>0.000471</td>\n",
       "      <td>4.714827e-04</td>\n",
       "      <td>0.009021</td>\n",
       "      <td>0.012548</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.003333</td>\n",
       "      <td>0.001333</td>\n",
       "      <td>0.960000</td>\n",
       "      <td>0.973460</td>\n",
       "      <td>SVC(C=10, cache_size=200, class_weight=None, c...</td>\n",
       "      <td>10</td>\n",
       "      <td>PCA(copy=True, iterated_power='auto', n_compon...</td>\n",
       "      <td>2</td>\n",
       "      <td>{u'classify__C': 10, u'reduce_dim': PCA(copy=T...</td>\n",
       "      <td>25</td>\n",
       "      <td>0.980392</td>\n",
       "      <td>0.959596</td>\n",
       "      <td>0.921569</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.979167</td>\n",
       "      <td>0.960784</td>\n",
       "      <td>0.001247</td>\n",
       "      <td>4.713704e-04</td>\n",
       "      <td>0.027588</td>\n",
       "      <td>0.018773</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.003667</td>\n",
       "      <td>0.000667</td>\n",
       "      <td>0.980000</td>\n",
       "      <td>0.973460</td>\n",
       "      <td>SVC(C=10, cache_size=200, class_weight=None, c...</td>\n",
       "      <td>10</td>\n",
       "      <td>PCA(copy=True, iterated_power='auto', n_compon...</td>\n",
       "      <td>3</td>\n",
       "      <td>{u'classify__C': 10, u'reduce_dim': PCA(copy=T...</td>\n",
       "      <td>1</td>\n",
       "      <td>0.980392</td>\n",
       "      <td>0.959596</td>\n",
       "      <td>0.960784</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.960784</td>\n",
       "      <td>0.001700</td>\n",
       "      <td>4.714266e-04</td>\n",
       "      <td>0.015925</td>\n",
       "      <td>0.018773</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.153667</td>\n",
       "      <td>0.002333</td>\n",
       "      <td>0.973333</td>\n",
       "      <td>0.966825</td>\n",
       "      <td>SVC(C=10, cache_size=200, class_weight=None, c...</td>\n",
       "      <td>10</td>\n",
       "      <td>NMF(alpha=0.0, beta_loss='frobenius', init=Non...</td>\n",
       "      <td>2</td>\n",
       "      <td>{u'classify__C': 10, u'reduce_dim': NMF(alpha=...</td>\n",
       "      <td>3</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.959596</td>\n",
       "      <td>0.941176</td>\n",
       "      <td>0.989899</td>\n",
       "      <td>0.979167</td>\n",
       "      <td>0.950980</td>\n",
       "      <td>0.082883</td>\n",
       "      <td>4.714266e-04</td>\n",
       "      <td>0.024581</td>\n",
       "      <td>0.016691</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.040000</td>\n",
       "      <td>0.003000</td>\n",
       "      <td>0.966667</td>\n",
       "      <td>0.953357</td>\n",
       "      <td>SVC(C=10, cache_size=200, class_weight=None, c...</td>\n",
       "      <td>10</td>\n",
       "      <td>NMF(alpha=0.0, beta_loss='frobenius', init=Non...</td>\n",
       "      <td>3</td>\n",
       "      <td>{u'classify__C': 10, u'reduce_dim': NMF(alpha=...</td>\n",
       "      <td>11</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.939394</td>\n",
       "      <td>0.921569</td>\n",
       "      <td>0.969697</td>\n",
       "      <td>0.979167</td>\n",
       "      <td>0.950980</td>\n",
       "      <td>0.016309</td>\n",
       "      <td>1.414280e-03</td>\n",
       "      <td>0.033456</td>\n",
       "      <td>0.012485</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.448667</td>\n",
       "      <td>0.004333</td>\n",
       "      <td>0.960000</td>\n",
       "      <td>0.960190</td>\n",
       "      <td>SVC(C=10, cache_size=200, class_weight=None, c...</td>\n",
       "      <td>10</td>\n",
       "      <td>Isomap(eigen_solver='auto', max_iter=None, n_c...</td>\n",
       "      <td>2</td>\n",
       "      <td>{u'classify__C': 10, u'reduce_dim': Isomap(eig...</td>\n",
       "      <td>25</td>\n",
       "      <td>0.980392</td>\n",
       "      <td>0.949495</td>\n",
       "      <td>0.921569</td>\n",
       "      <td>0.989899</td>\n",
       "      <td>0.979167</td>\n",
       "      <td>0.941176</td>\n",
       "      <td>0.387964</td>\n",
       "      <td>4.714266e-04</td>\n",
       "      <td>0.027588</td>\n",
       "      <td>0.021280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0.087333</td>\n",
       "      <td>0.004333</td>\n",
       "      <td>0.960000</td>\n",
       "      <td>0.956922</td>\n",
       "      <td>SVC(C=10, cache_size=200, class_weight=None, c...</td>\n",
       "      <td>10</td>\n",
       "      <td>Isomap(eigen_solver='auto', max_iter=None, n_c...</td>\n",
       "      <td>3</td>\n",
       "      <td>{u'classify__C': 10, u'reduce_dim': Isomap(eig...</td>\n",
       "      <td>25</td>\n",
       "      <td>0.980392</td>\n",
       "      <td>0.949495</td>\n",
       "      <td>0.921569</td>\n",
       "      <td>0.989899</td>\n",
       "      <td>0.979167</td>\n",
       "      <td>0.931373</td>\n",
       "      <td>0.103042</td>\n",
       "      <td>4.713704e-04</td>\n",
       "      <td>0.027588</td>\n",
       "      <td>0.024464</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0.003667</td>\n",
       "      <td>0.001000</td>\n",
       "      <td>0.960000</td>\n",
       "      <td>0.973559</td>\n",
       "      <td>SVC(C=10, cache_size=200, class_weight=None, c...</td>\n",
       "      <td>10</td>\n",
       "      <td>TruncatedSVD(algorithm='randomized', n_compone...</td>\n",
       "      <td>2</td>\n",
       "      <td>{u'classify__C': 10, u'reduce_dim': TruncatedS...</td>\n",
       "      <td>25</td>\n",
       "      <td>0.980392</td>\n",
       "      <td>0.969697</td>\n",
       "      <td>0.921569</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.979167</td>\n",
       "      <td>0.950980</td>\n",
       "      <td>0.000471</td>\n",
       "      <td>1.123916e-07</td>\n",
       "      <td>0.027588</td>\n",
       "      <td>0.020198</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0.236333</td>\n",
       "      <td>0.001000</td>\n",
       "      <td>0.980000</td>\n",
       "      <td>0.973460</td>\n",
       "      <td>SVC(C=10, cache_size=200, class_weight=None, c...</td>\n",
       "      <td>10</td>\n",
       "      <td>TruncatedSVD(algorithm='randomized', n_compone...</td>\n",
       "      <td>3</td>\n",
       "      <td>{u'classify__C': 10, u'reduce_dim': TruncatedS...</td>\n",
       "      <td>1</td>\n",
       "      <td>0.980392</td>\n",
       "      <td>0.959596</td>\n",
       "      <td>0.960784</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.960784</td>\n",
       "      <td>0.298680</td>\n",
       "      <td>1.123916e-07</td>\n",
       "      <td>0.015925</td>\n",
       "      <td>0.018773</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>0.002667</td>\n",
       "      <td>0.000333</td>\n",
       "      <td>0.953333</td>\n",
       "      <td>0.980095</td>\n",
       "      <td>SVC(C=10, cache_size=200, class_weight=None, c...</td>\n",
       "      <td>100</td>\n",
       "      <td>PCA(copy=True, iterated_power='auto', n_compon...</td>\n",
       "      <td>2</td>\n",
       "      <td>{u'classify__C': 100, u'reduce_dim': PCA(copy=...</td>\n",
       "      <td>32</td>\n",
       "      <td>0.980392</td>\n",
       "      <td>0.969697</td>\n",
       "      <td>0.901961</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.979167</td>\n",
       "      <td>0.970588</td>\n",
       "      <td>0.000471</td>\n",
       "      <td>4.714827e-04</td>\n",
       "      <td>0.036876</td>\n",
       "      <td>0.014080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0.014333</td>\n",
       "      <td>0.005333</td>\n",
       "      <td>0.966667</td>\n",
       "      <td>0.989998</td>\n",
       "      <td>SVC(C=10, cache_size=200, class_weight=None, c...</td>\n",
       "      <td>100</td>\n",
       "      <td>PCA(copy=True, iterated_power='auto', n_compon...</td>\n",
       "      <td>3</td>\n",
       "      <td>{u'classify__C': 100, u'reduce_dim': PCA(copy=...</td>\n",
       "      <td>11</td>\n",
       "      <td>0.980392</td>\n",
       "      <td>0.979798</td>\n",
       "      <td>0.921569</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.990196</td>\n",
       "      <td>0.016740</td>\n",
       "      <td>6.128208e-03</td>\n",
       "      <td>0.033333</td>\n",
       "      <td>0.008249</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0.035667</td>\n",
       "      <td>0.002333</td>\n",
       "      <td>0.966667</td>\n",
       "      <td>0.976728</td>\n",
       "      <td>SVC(C=10, cache_size=200, class_weight=None, c...</td>\n",
       "      <td>100</td>\n",
       "      <td>NMF(alpha=0.0, beta_loss='frobenius', init=Non...</td>\n",
       "      <td>2</td>\n",
       "      <td>{u'classify__C': 100, u'reduce_dim': NMF(alpha...</td>\n",
       "      <td>11</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.959596</td>\n",
       "      <td>0.921569</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.979167</td>\n",
       "      <td>0.970588</td>\n",
       "      <td>0.017211</td>\n",
       "      <td>1.247214e-03</td>\n",
       "      <td>0.033456</td>\n",
       "      <td>0.017057</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0.113667</td>\n",
       "      <td>0.002000</td>\n",
       "      <td>0.973333</td>\n",
       "      <td>0.976827</td>\n",
       "      <td>SVC(C=10, cache_size=200, class_weight=None, c...</td>\n",
       "      <td>100</td>\n",
       "      <td>NMF(alpha=0.0, beta_loss='frobenius', init=Non...</td>\n",
       "      <td>3</td>\n",
       "      <td>{u'classify__C': 100, u'reduce_dim': NMF(alpha...</td>\n",
       "      <td>3</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.979798</td>\n",
       "      <td>0.941176</td>\n",
       "      <td>0.989899</td>\n",
       "      <td>0.979167</td>\n",
       "      <td>0.960784</td>\n",
       "      <td>0.075650</td>\n",
       "      <td>1.123916e-07</td>\n",
       "      <td>0.024581</td>\n",
       "      <td>0.012070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0.118667</td>\n",
       "      <td>0.007667</td>\n",
       "      <td>0.946667</td>\n",
       "      <td>0.973460</td>\n",
       "      <td>SVC(C=10, cache_size=200, class_weight=None, c...</td>\n",
       "      <td>100</td>\n",
       "      <td>Isomap(eigen_solver='auto', max_iter=None, n_c...</td>\n",
       "      <td>2</td>\n",
       "      <td>{u'classify__C': 100, u'reduce_dim': Isomap(ei...</td>\n",
       "      <td>40</td>\n",
       "      <td>0.960784</td>\n",
       "      <td>0.959596</td>\n",
       "      <td>0.901961</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.979167</td>\n",
       "      <td>0.960784</td>\n",
       "      <td>0.118969</td>\n",
       "      <td>5.906653e-03</td>\n",
       "      <td>0.032944</td>\n",
       "      <td>0.018773</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>0.053667</td>\n",
       "      <td>0.004333</td>\n",
       "      <td>0.953333</td>\n",
       "      <td>0.970093</td>\n",
       "      <td>SVC(C=10, cache_size=200, class_weight=None, c...</td>\n",
       "      <td>100</td>\n",
       "      <td>Isomap(eigen_solver='auto', max_iter=None, n_c...</td>\n",
       "      <td>3</td>\n",
       "      <td>{u'classify__C': 100, u'reduce_dim': Isomap(ei...</td>\n",
       "      <td>32</td>\n",
       "      <td>0.980392</td>\n",
       "      <td>0.959596</td>\n",
       "      <td>0.901961</td>\n",
       "      <td>0.989899</td>\n",
       "      <td>0.979167</td>\n",
       "      <td>0.960784</td>\n",
       "      <td>0.019482</td>\n",
       "      <td>4.713704e-04</td>\n",
       "      <td>0.036876</td>\n",
       "      <td>0.014013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>0.004000</td>\n",
       "      <td>0.000667</td>\n",
       "      <td>0.953333</td>\n",
       "      <td>0.980095</td>\n",
       "      <td>SVC(C=10, cache_size=200, class_weight=None, c...</td>\n",
       "      <td>100</td>\n",
       "      <td>TruncatedSVD(algorithm='randomized', n_compone...</td>\n",
       "      <td>2</td>\n",
       "      <td>{u'classify__C': 100, u'reduce_dim': Truncated...</td>\n",
       "      <td>32</td>\n",
       "      <td>0.980392</td>\n",
       "      <td>0.969697</td>\n",
       "      <td>0.901961</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.979167</td>\n",
       "      <td>0.970588</td>\n",
       "      <td>0.000817</td>\n",
       "      <td>4.713704e-04</td>\n",
       "      <td>0.036876</td>\n",
       "      <td>0.014080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>0.004667</td>\n",
       "      <td>0.000667</td>\n",
       "      <td>0.966667</td>\n",
       "      <td>0.989998</td>\n",
       "      <td>SVC(C=10, cache_size=200, class_weight=None, c...</td>\n",
       "      <td>100</td>\n",
       "      <td>TruncatedSVD(algorithm='randomized', n_compone...</td>\n",
       "      <td>3</td>\n",
       "      <td>{u'classify__C': 100, u'reduce_dim': Truncated...</td>\n",
       "      <td>11</td>\n",
       "      <td>0.980392</td>\n",
       "      <td>0.979798</td>\n",
       "      <td>0.921569</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.990196</td>\n",
       "      <td>0.000471</td>\n",
       "      <td>4.713704e-04</td>\n",
       "      <td>0.033333</td>\n",
       "      <td>0.008249</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>0.004000</td>\n",
       "      <td>0.001333</td>\n",
       "      <td>0.946667</td>\n",
       "      <td>0.986730</td>\n",
       "      <td>SVC(C=10, cache_size=200, class_weight=None, c...</td>\n",
       "      <td>1000</td>\n",
       "      <td>PCA(copy=True, iterated_power='auto', n_compon...</td>\n",
       "      <td>2</td>\n",
       "      <td>{u'classify__C': 1000, u'reduce_dim': PCA(copy...</td>\n",
       "      <td>40</td>\n",
       "      <td>0.960784</td>\n",
       "      <td>0.979798</td>\n",
       "      <td>0.901961</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.979167</td>\n",
       "      <td>0.980392</td>\n",
       "      <td>0.001414</td>\n",
       "      <td>4.714827e-04</td>\n",
       "      <td>0.032944</td>\n",
       "      <td>0.009386</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0.003333</td>\n",
       "      <td>0.001333</td>\n",
       "      <td>0.966667</td>\n",
       "      <td>0.993365</td>\n",
       "      <td>SVC(C=10, cache_size=200, class_weight=None, c...</td>\n",
       "      <td>1000</td>\n",
       "      <td>PCA(copy=True, iterated_power='auto', n_compon...</td>\n",
       "      <td>3</td>\n",
       "      <td>{u'classify__C': 1000, u'reduce_dim': PCA(copy...</td>\n",
       "      <td>11</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.989899</td>\n",
       "      <td>0.921569</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.979167</td>\n",
       "      <td>0.990196</td>\n",
       "      <td>0.001247</td>\n",
       "      <td>1.247235e-03</td>\n",
       "      <td>0.033456</td>\n",
       "      <td>0.004693</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>0.054667</td>\n",
       "      <td>0.001667</td>\n",
       "      <td>0.953333</td>\n",
       "      <td>0.983363</td>\n",
       "      <td>SVC(C=10, cache_size=200, class_weight=None, c...</td>\n",
       "      <td>1000</td>\n",
       "      <td>NMF(alpha=0.0, beta_loss='frobenius', init=Non...</td>\n",
       "      <td>2</td>\n",
       "      <td>{u'classify__C': 1000, u'reduce_dim': NMF(alph...</td>\n",
       "      <td>32</td>\n",
       "      <td>0.980392</td>\n",
       "      <td>0.969697</td>\n",
       "      <td>0.901961</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.979167</td>\n",
       "      <td>0.980392</td>\n",
       "      <td>0.010209</td>\n",
       "      <td>4.714266e-04</td>\n",
       "      <td>0.036876</td>\n",
       "      <td>0.012548</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>0.102333</td>\n",
       "      <td>0.001667</td>\n",
       "      <td>0.973333</td>\n",
       "      <td>0.976728</td>\n",
       "      <td>SVC(C=10, cache_size=200, class_weight=None, c...</td>\n",
       "      <td>1000</td>\n",
       "      <td>NMF(alpha=0.0, beta_loss='frobenius', init=Non...</td>\n",
       "      <td>3</td>\n",
       "      <td>{u'classify__C': 1000, u'reduce_dim': NMF(alph...</td>\n",
       "      <td>3</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.959596</td>\n",
       "      <td>0.921569</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.970588</td>\n",
       "      <td>0.037853</td>\n",
       "      <td>4.714266e-04</td>\n",
       "      <td>0.037154</td>\n",
       "      <td>0.017057</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>0.021000</td>\n",
       "      <td>0.005000</td>\n",
       "      <td>0.933333</td>\n",
       "      <td>0.970192</td>\n",
       "      <td>SVC(C=10, cache_size=200, class_weight=None, c...</td>\n",
       "      <td>1000</td>\n",
       "      <td>Isomap(eigen_solver='auto', max_iter=None, n_c...</td>\n",
       "      <td>2</td>\n",
       "      <td>{u'classify__C': 1000, u'reduce_dim': Isomap(e...</td>\n",
       "      <td>48</td>\n",
       "      <td>0.960784</td>\n",
       "      <td>0.959596</td>\n",
       "      <td>0.862745</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.979167</td>\n",
       "      <td>0.950980</td>\n",
       "      <td>0.006377</td>\n",
       "      <td>8.163401e-04</td>\n",
       "      <td>0.051211</td>\n",
       "      <td>0.021369</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>0.017667</td>\n",
       "      <td>0.004667</td>\n",
       "      <td>0.933333</td>\n",
       "      <td>0.983462</td>\n",
       "      <td>SVC(C=10, cache_size=200, class_weight=None, c...</td>\n",
       "      <td>1000</td>\n",
       "      <td>Isomap(eigen_solver='auto', max_iter=None, n_c...</td>\n",
       "      <td>3</td>\n",
       "      <td>{u'classify__C': 1000, u'reduce_dim': Isomap(e...</td>\n",
       "      <td>48</td>\n",
       "      <td>0.960784</td>\n",
       "      <td>0.979798</td>\n",
       "      <td>0.862745</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.979167</td>\n",
       "      <td>0.970588</td>\n",
       "      <td>0.010143</td>\n",
       "      <td>4.714266e-04</td>\n",
       "      <td>0.051211</td>\n",
       "      <td>0.012284</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>0.149000</td>\n",
       "      <td>0.002000</td>\n",
       "      <td>0.966667</td>\n",
       "      <td>0.970093</td>\n",
       "      <td>LinearSVC(C=1.0, class_weight=None, dual=True,...</td>\n",
       "      <td>1</td>\n",
       "      <td>NMF(alpha=0.0, beta_loss='frobenius', init=Non...</td>\n",
       "      <td>2</td>\n",
       "      <td>{u'classify__C': 1, u'reduce_dim': NMF(alpha=0...</td>\n",
       "      <td>11</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.949495</td>\n",
       "      <td>0.901961</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.960784</td>\n",
       "      <td>0.082660</td>\n",
       "      <td>1.123916e-07</td>\n",
       "      <td>0.046442</td>\n",
       "      <td>0.021644</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>0.108667</td>\n",
       "      <td>0.001667</td>\n",
       "      <td>0.953333</td>\n",
       "      <td>0.963458</td>\n",
       "      <td>LinearSVC(C=1.0, class_weight=None, dual=True,...</td>\n",
       "      <td>1</td>\n",
       "      <td>NMF(alpha=0.0, beta_loss='frobenius', init=Non...</td>\n",
       "      <td>3</td>\n",
       "      <td>{u'classify__C': 1, u'reduce_dim': NMF(alpha=0...</td>\n",
       "      <td>32</td>\n",
       "      <td>0.980392</td>\n",
       "      <td>0.949495</td>\n",
       "      <td>0.882353</td>\n",
       "      <td>0.989899</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.950980</td>\n",
       "      <td>0.061157</td>\n",
       "      <td>4.714266e-04</td>\n",
       "      <td>0.051564</td>\n",
       "      <td>0.018706</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>0.742667</td>\n",
       "      <td>0.003667</td>\n",
       "      <td>0.920000</td>\n",
       "      <td>0.930184</td>\n",
       "      <td>LinearSVC(C=1.0, class_weight=None, dual=True,...</td>\n",
       "      <td>1</td>\n",
       "      <td>Isomap(eigen_solver='auto', max_iter=None, n_c...</td>\n",
       "      <td>2</td>\n",
       "      <td>{u'classify__C': 1, u'reduce_dim': Isomap(eige...</td>\n",
       "      <td>57</td>\n",
       "      <td>0.901961</td>\n",
       "      <td>0.898990</td>\n",
       "      <td>0.901961</td>\n",
       "      <td>0.979798</td>\n",
       "      <td>0.958333</td>\n",
       "      <td>0.911765</td>\n",
       "      <td>0.377928</td>\n",
       "      <td>4.715951e-04</td>\n",
       "      <td>0.026296</td>\n",
       "      <td>0.035468</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>0.148000</td>\n",
       "      <td>0.003667</td>\n",
       "      <td>0.933333</td>\n",
       "      <td>0.933551</td>\n",
       "      <td>LinearSVC(C=1.0, class_weight=None, dual=True,...</td>\n",
       "      <td>1</td>\n",
       "      <td>Isomap(eigen_solver='auto', max_iter=None, n_c...</td>\n",
       "      <td>3</td>\n",
       "      <td>{u'classify__C': 1, u'reduce_dim': Isomap(eige...</td>\n",
       "      <td>48</td>\n",
       "      <td>0.941176</td>\n",
       "      <td>0.909091</td>\n",
       "      <td>0.901961</td>\n",
       "      <td>0.979798</td>\n",
       "      <td>0.958333</td>\n",
       "      <td>0.911765</td>\n",
       "      <td>0.015895</td>\n",
       "      <td>4.713704e-04</td>\n",
       "      <td>0.023570</td>\n",
       "      <td>0.032720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>0.062000</td>\n",
       "      <td>0.000667</td>\n",
       "      <td>0.966667</td>\n",
       "      <td>0.976728</td>\n",
       "      <td>LinearSVC(C=1.0, class_weight=None, dual=True,...</td>\n",
       "      <td>1</td>\n",
       "      <td>TruncatedSVD(algorithm='randomized', n_compone...</td>\n",
       "      <td>2</td>\n",
       "      <td>{u'classify__C': 1, u'reduce_dim': TruncatedSV...</td>\n",
       "      <td>11</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.959596</td>\n",
       "      <td>0.901961</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.970588</td>\n",
       "      <td>0.069296</td>\n",
       "      <td>4.714266e-04</td>\n",
       "      <td>0.046442</td>\n",
       "      <td>0.017057</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>0.036000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.973333</td>\n",
       "      <td>0.973361</td>\n",
       "      <td>LinearSVC(C=1.0, class_weight=None, dual=True,...</td>\n",
       "      <td>1</td>\n",
       "      <td>TruncatedSVD(algorithm='randomized', n_compone...</td>\n",
       "      <td>3</td>\n",
       "      <td>{u'classify__C': 1, u'reduce_dim': TruncatedSV...</td>\n",
       "      <td>3</td>\n",
       "      <td>0.980392</td>\n",
       "      <td>0.969697</td>\n",
       "      <td>0.960784</td>\n",
       "      <td>0.979798</td>\n",
       "      <td>0.979167</td>\n",
       "      <td>0.970588</td>\n",
       "      <td>0.017205</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.009021</td>\n",
       "      <td>0.004566</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>0.009667</td>\n",
       "      <td>0.001333</td>\n",
       "      <td>0.953333</td>\n",
       "      <td>0.966726</td>\n",
       "      <td>LinearSVC(C=1.0, class_weight=None, dual=True,...</td>\n",
       "      <td>10</td>\n",
       "      <td>PCA(copy=True, iterated_power='auto', n_compon...</td>\n",
       "      <td>2</td>\n",
       "      <td>{u'classify__C': 10, u'reduce_dim': PCA(copy=T...</td>\n",
       "      <td>32</td>\n",
       "      <td>0.960784</td>\n",
       "      <td>0.939394</td>\n",
       "      <td>0.921569</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.979167</td>\n",
       "      <td>0.960784</td>\n",
       "      <td>0.000471</td>\n",
       "      <td>4.713704e-04</td>\n",
       "      <td>0.023989</td>\n",
       "      <td>0.025097</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>0.010667</td>\n",
       "      <td>0.000667</td>\n",
       "      <td>0.973333</td>\n",
       "      <td>0.976728</td>\n",
       "      <td>LinearSVC(C=1.0, class_weight=None, dual=True,...</td>\n",
       "      <td>10</td>\n",
       "      <td>PCA(copy=True, iterated_power='auto', n_compon...</td>\n",
       "      <td>3</td>\n",
       "      <td>{u'classify__C': 10, u'reduce_dim': PCA(copy=T...</td>\n",
       "      <td>3</td>\n",
       "      <td>0.980392</td>\n",
       "      <td>0.959596</td>\n",
       "      <td>0.941176</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.970588</td>\n",
       "      <td>0.002357</td>\n",
       "      <td>4.714266e-04</td>\n",
       "      <td>0.024415</td>\n",
       "      <td>0.017057</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>0.058667</td>\n",
       "      <td>0.002000</td>\n",
       "      <td>0.960000</td>\n",
       "      <td>0.976728</td>\n",
       "      <td>LinearSVC(C=1.0, class_weight=None, dual=True,...</td>\n",
       "      <td>10</td>\n",
       "      <td>NMF(alpha=0.0, beta_loss='frobenius', init=Non...</td>\n",
       "      <td>2</td>\n",
       "      <td>{u'classify__C': 10, u'reduce_dim': NMF(alpha=...</td>\n",
       "      <td>25</td>\n",
       "      <td>0.980392</td>\n",
       "      <td>0.959596</td>\n",
       "      <td>0.921569</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.979167</td>\n",
       "      <td>0.970588</td>\n",
       "      <td>0.014055</td>\n",
       "      <td>1.123916e-07</td>\n",
       "      <td>0.027588</td>\n",
       "      <td>0.017057</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>0.046333</td>\n",
       "      <td>0.013667</td>\n",
       "      <td>0.966667</td>\n",
       "      <td>0.980095</td>\n",
       "      <td>LinearSVC(C=1.0, class_weight=None, dual=True,...</td>\n",
       "      <td>10</td>\n",
       "      <td>NMF(alpha=0.0, beta_loss='frobenius', init=Non...</td>\n",
       "      <td>3</td>\n",
       "      <td>{u'classify__C': 10, u'reduce_dim': NMF(alpha=...</td>\n",
       "      <td>11</td>\n",
       "      <td>0.980392</td>\n",
       "      <td>0.969697</td>\n",
       "      <td>0.921569</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.970588</td>\n",
       "      <td>0.016111</td>\n",
       "      <td>1.510706e-02</td>\n",
       "      <td>0.033333</td>\n",
       "      <td>0.014080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>0.272000</td>\n",
       "      <td>0.004667</td>\n",
       "      <td>0.926667</td>\n",
       "      <td>0.936819</td>\n",
       "      <td>LinearSVC(C=1.0, class_weight=None, dual=True,...</td>\n",
       "      <td>10</td>\n",
       "      <td>Isomap(eigen_solver='auto', max_iter=None, n_c...</td>\n",
       "      <td>2</td>\n",
       "      <td>{u'classify__C': 10, u'reduce_dim': Isomap(eig...</td>\n",
       "      <td>55</td>\n",
       "      <td>0.921569</td>\n",
       "      <td>0.909091</td>\n",
       "      <td>0.901961</td>\n",
       "      <td>0.979798</td>\n",
       "      <td>0.958333</td>\n",
       "      <td>0.921569</td>\n",
       "      <td>0.120044</td>\n",
       "      <td>4.713704e-04</td>\n",
       "      <td>0.023179</td>\n",
       "      <td>0.030815</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>0.085667</td>\n",
       "      <td>0.004000</td>\n",
       "      <td>0.933333</td>\n",
       "      <td>0.943553</td>\n",
       "      <td>LinearSVC(C=1.0, class_weight=None, dual=True,...</td>\n",
       "      <td>10</td>\n",
       "      <td>Isomap(eigen_solver='auto', max_iter=None, n_c...</td>\n",
       "      <td>3</td>\n",
       "      <td>{u'classify__C': 10, u'reduce_dim': Isomap(eig...</td>\n",
       "      <td>48</td>\n",
       "      <td>0.941176</td>\n",
       "      <td>0.929293</td>\n",
       "      <td>0.901961</td>\n",
       "      <td>0.979798</td>\n",
       "      <td>0.958333</td>\n",
       "      <td>0.921569</td>\n",
       "      <td>0.044515</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.023570</td>\n",
       "      <td>0.025822</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>0.013333</td>\n",
       "      <td>0.000667</td>\n",
       "      <td>0.960000</td>\n",
       "      <td>0.966726</td>\n",
       "      <td>LinearSVC(C=1.0, class_weight=None, dual=True,...</td>\n",
       "      <td>10</td>\n",
       "      <td>TruncatedSVD(algorithm='randomized', n_compone...</td>\n",
       "      <td>2</td>\n",
       "      <td>{u'classify__C': 10, u'reduce_dim': TruncatedS...</td>\n",
       "      <td>25</td>\n",
       "      <td>0.980392</td>\n",
       "      <td>0.949495</td>\n",
       "      <td>0.921569</td>\n",
       "      <td>0.989899</td>\n",
       "      <td>0.979167</td>\n",
       "      <td>0.960784</td>\n",
       "      <td>0.000471</td>\n",
       "      <td>4.714266e-04</td>\n",
       "      <td>0.027588</td>\n",
       "      <td>0.017022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>0.024333</td>\n",
       "      <td>0.000667</td>\n",
       "      <td>0.966667</td>\n",
       "      <td>0.963260</td>\n",
       "      <td>LinearSVC(C=1.0, class_weight=None, dual=True,...</td>\n",
       "      <td>10</td>\n",
       "      <td>TruncatedSVD(algorithm='randomized', n_compone...</td>\n",
       "      <td>3</td>\n",
       "      <td>{u'classify__C': 10, u'reduce_dim': TruncatedS...</td>\n",
       "      <td>11</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.919192</td>\n",
       "      <td>0.921569</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.979167</td>\n",
       "      <td>0.970588</td>\n",
       "      <td>0.016740</td>\n",
       "      <td>4.713704e-04</td>\n",
       "      <td>0.033456</td>\n",
       "      <td>0.033394</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>0.033333</td>\n",
       "      <td>0.001000</td>\n",
       "      <td>0.946667</td>\n",
       "      <td>0.956724</td>\n",
       "      <td>LinearSVC(C=1.0, class_weight=None, dual=True,...</td>\n",
       "      <td>100</td>\n",
       "      <td>PCA(copy=True, iterated_power='auto', n_compon...</td>\n",
       "      <td>2</td>\n",
       "      <td>{u'classify__C': 100, u'reduce_dim': PCA(copy=...</td>\n",
       "      <td>40</td>\n",
       "      <td>0.941176</td>\n",
       "      <td>0.919192</td>\n",
       "      <td>0.921569</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.979167</td>\n",
       "      <td>0.950980</td>\n",
       "      <td>0.031584</td>\n",
       "      <td>8.165347e-04</td>\n",
       "      <td>0.023715</td>\n",
       "      <td>0.033239</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>0.010667</td>\n",
       "      <td>0.001000</td>\n",
       "      <td>0.966667</td>\n",
       "      <td>0.973460</td>\n",
       "      <td>LinearSVC(C=1.0, class_weight=None, dual=True,...</td>\n",
       "      <td>100</td>\n",
       "      <td>PCA(copy=True, iterated_power='auto', n_compon...</td>\n",
       "      <td>3</td>\n",
       "      <td>{u'classify__C': 100, u'reduce_dim': PCA(copy=...</td>\n",
       "      <td>11</td>\n",
       "      <td>0.980392</td>\n",
       "      <td>0.959596</td>\n",
       "      <td>0.941176</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.979167</td>\n",
       "      <td>0.960784</td>\n",
       "      <td>0.000471</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.018302</td>\n",
       "      <td>0.018773</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>0.037333</td>\n",
       "      <td>0.003000</td>\n",
       "      <td>0.953333</td>\n",
       "      <td>0.969994</td>\n",
       "      <td>LinearSVC(C=1.0, class_weight=None, dual=True,...</td>\n",
       "      <td>100</td>\n",
       "      <td>NMF(alpha=0.0, beta_loss='frobenius', init=Non...</td>\n",
       "      <td>2</td>\n",
       "      <td>{u'classify__C': 100, u'reduce_dim': NMF(alpha...</td>\n",
       "      <td>32</td>\n",
       "      <td>0.980392</td>\n",
       "      <td>0.939394</td>\n",
       "      <td>0.901961</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.979167</td>\n",
       "      <td>0.970588</td>\n",
       "      <td>0.002055</td>\n",
       "      <td>1.414111e-03</td>\n",
       "      <td>0.036876</td>\n",
       "      <td>0.024746</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>0.094667</td>\n",
       "      <td>0.002000</td>\n",
       "      <td>0.960000</td>\n",
       "      <td>0.976728</td>\n",
       "      <td>LinearSVC(C=1.0, class_weight=None, dual=True,...</td>\n",
       "      <td>100</td>\n",
       "      <td>NMF(alpha=0.0, beta_loss='frobenius', init=Non...</td>\n",
       "      <td>3</td>\n",
       "      <td>{u'classify__C': 100, u'reduce_dim': NMF(alpha...</td>\n",
       "      <td>25</td>\n",
       "      <td>0.980392</td>\n",
       "      <td>0.959596</td>\n",
       "      <td>0.921569</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.979167</td>\n",
       "      <td>0.970588</td>\n",
       "      <td>0.033370</td>\n",
       "      <td>1.123916e-07</td>\n",
       "      <td>0.027588</td>\n",
       "      <td>0.017057</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>0.147333</td>\n",
       "      <td>0.003333</td>\n",
       "      <td>0.926667</td>\n",
       "      <td>0.890176</td>\n",
       "      <td>LinearSVC(C=1.0, class_weight=None, dual=True,...</td>\n",
       "      <td>100</td>\n",
       "      <td>Isomap(eigen_solver='auto', max_iter=None, n_c...</td>\n",
       "      <td>2</td>\n",
       "      <td>{u'classify__C': 100, u'reduce_dim': Isomap(ei...</td>\n",
       "      <td>55</td>\n",
       "      <td>0.921569</td>\n",
       "      <td>0.868687</td>\n",
       "      <td>0.921569</td>\n",
       "      <td>0.929293</td>\n",
       "      <td>0.937500</td>\n",
       "      <td>0.872549</td>\n",
       "      <td>0.092903</td>\n",
       "      <td>4.713704e-04</td>\n",
       "      <td>0.007432</td>\n",
       "      <td>0.027705</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>0.158333</td>\n",
       "      <td>0.004000</td>\n",
       "      <td>0.886667</td>\n",
       "      <td>0.893345</td>\n",
       "      <td>LinearSVC(C=1.0, class_weight=None, dual=True,...</td>\n",
       "      <td>100</td>\n",
       "      <td>Isomap(eigen_solver='auto', max_iter=None, n_c...</td>\n",
       "      <td>3</td>\n",
       "      <td>{u'classify__C': 100, u'reduce_dim': Isomap(ei...</td>\n",
       "      <td>62</td>\n",
       "      <td>0.941176</td>\n",
       "      <td>0.929293</td>\n",
       "      <td>0.745098</td>\n",
       "      <td>0.858586</td>\n",
       "      <td>0.979167</td>\n",
       "      <td>0.892157</td>\n",
       "      <td>0.059918</td>\n",
       "      <td>8.164374e-04</td>\n",
       "      <td>0.102774</td>\n",
       "      <td>0.028878</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>0.164000</td>\n",
       "      <td>0.001000</td>\n",
       "      <td>0.913333</td>\n",
       "      <td>0.916914</td>\n",
       "      <td>LinearSVC(C=1.0, class_weight=None, dual=True,...</td>\n",
       "      <td>100</td>\n",
       "      <td>TruncatedSVD(algorithm='randomized', n_compone...</td>\n",
       "      <td>2</td>\n",
       "      <td>{u'classify__C': 100, u'reduce_dim': Truncated...</td>\n",
       "      <td>58</td>\n",
       "      <td>0.980392</td>\n",
       "      <td>0.959596</td>\n",
       "      <td>0.843137</td>\n",
       "      <td>0.898990</td>\n",
       "      <td>0.916667</td>\n",
       "      <td>0.892157</td>\n",
       "      <td>0.073025</td>\n",
       "      <td>1.123916e-07</td>\n",
       "      <td>0.056638</td>\n",
       "      <td>0.030309</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>0.296000</td>\n",
       "      <td>0.000333</td>\n",
       "      <td>0.933333</td>\n",
       "      <td>0.950188</td>\n",
       "      <td>LinearSVC(C=1.0, class_weight=None, dual=True,...</td>\n",
       "      <td>100</td>\n",
       "      <td>TruncatedSVD(algorithm='randomized', n_compone...</td>\n",
       "      <td>3</td>\n",
       "      <td>{u'classify__C': 100, u'reduce_dim': Truncated...</td>\n",
       "      <td>48</td>\n",
       "      <td>0.960784</td>\n",
       "      <td>0.939394</td>\n",
       "      <td>0.862745</td>\n",
       "      <td>0.979798</td>\n",
       "      <td>0.979167</td>\n",
       "      <td>0.931373</td>\n",
       "      <td>0.122695</td>\n",
       "      <td>4.713704e-04</td>\n",
       "      <td>0.051211</td>\n",
       "      <td>0.021192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>0.039667</td>\n",
       "      <td>0.000333</td>\n",
       "      <td>0.940000</td>\n",
       "      <td>0.956724</td>\n",
       "      <td>LinearSVC(C=1.0, class_weight=None, dual=True,...</td>\n",
       "      <td>1000</td>\n",
       "      <td>PCA(copy=True, iterated_power='auto', n_compon...</td>\n",
       "      <td>2</td>\n",
       "      <td>{u'classify__C': 1000, u'reduce_dim': PCA(copy...</td>\n",
       "      <td>45</td>\n",
       "      <td>0.960784</td>\n",
       "      <td>0.919192</td>\n",
       "      <td>0.882353</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.979167</td>\n",
       "      <td>0.950980</td>\n",
       "      <td>0.027633</td>\n",
       "      <td>4.714827e-04</td>\n",
       "      <td>0.042043</td>\n",
       "      <td>0.033239</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>0.021667</td>\n",
       "      <td>0.000667</td>\n",
       "      <td>0.946667</td>\n",
       "      <td>0.946821</td>\n",
       "      <td>LinearSVC(C=1.0, class_weight=None, dual=True,...</td>\n",
       "      <td>1000</td>\n",
       "      <td>PCA(copy=True, iterated_power='auto', n_compon...</td>\n",
       "      <td>3</td>\n",
       "      <td>{u'classify__C': 1000, u'reduce_dim': PCA(copy...</td>\n",
       "      <td>40</td>\n",
       "      <td>0.980392</td>\n",
       "      <td>0.929293</td>\n",
       "      <td>0.921569</td>\n",
       "      <td>0.979798</td>\n",
       "      <td>0.937500</td>\n",
       "      <td>0.931373</td>\n",
       "      <td>0.009843</td>\n",
       "      <td>4.714266e-04</td>\n",
       "      <td>0.025055</td>\n",
       "      <td>0.023334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>0.063000</td>\n",
       "      <td>0.002000</td>\n",
       "      <td>0.893333</td>\n",
       "      <td>0.936522</td>\n",
       "      <td>LinearSVC(C=1.0, class_weight=None, dual=True,...</td>\n",
       "      <td>1000</td>\n",
       "      <td>NMF(alpha=0.0, beta_loss='frobenius', init=Non...</td>\n",
       "      <td>2</td>\n",
       "      <td>{u'classify__C': 1000, u'reduce_dim': NMF(alph...</td>\n",
       "      <td>61</td>\n",
       "      <td>0.823529</td>\n",
       "      <td>0.868687</td>\n",
       "      <td>0.901961</td>\n",
       "      <td>0.989899</td>\n",
       "      <td>0.958333</td>\n",
       "      <td>0.950980</td>\n",
       "      <td>0.004546</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.055082</td>\n",
       "      <td>0.050530</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>0.032667</td>\n",
       "      <td>0.004333</td>\n",
       "      <td>0.946667</td>\n",
       "      <td>0.966825</td>\n",
       "      <td>LinearSVC(C=1.0, class_weight=None, dual=True,...</td>\n",
       "      <td>1000</td>\n",
       "      <td>NMF(alpha=0.0, beta_loss='frobenius', init=Non...</td>\n",
       "      <td>3</td>\n",
       "      <td>{u'classify__C': 1000, u'reduce_dim': NMF(alph...</td>\n",
       "      <td>40</td>\n",
       "      <td>0.960784</td>\n",
       "      <td>0.949495</td>\n",
       "      <td>0.921569</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.958333</td>\n",
       "      <td>0.950980</td>\n",
       "      <td>0.000471</td>\n",
       "      <td>4.027679e-03</td>\n",
       "      <td>0.018041</td>\n",
       "      <td>0.023466</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>0.052000</td>\n",
       "      <td>0.003333</td>\n",
       "      <td>0.913333</td>\n",
       "      <td>0.889978</td>\n",
       "      <td>LinearSVC(C=1.0, class_weight=None, dual=True,...</td>\n",
       "      <td>1000</td>\n",
       "      <td>Isomap(eigen_solver='auto', max_iter=None, n_c...</td>\n",
       "      <td>2</td>\n",
       "      <td>{u'classify__C': 1000, u'reduce_dim': Isomap(e...</td>\n",
       "      <td>58</td>\n",
       "      <td>0.901961</td>\n",
       "      <td>0.848485</td>\n",
       "      <td>0.921569</td>\n",
       "      <td>0.929293</td>\n",
       "      <td>0.916667</td>\n",
       "      <td>0.892157</td>\n",
       "      <td>0.040357</td>\n",
       "      <td>4.713704e-04</td>\n",
       "      <td>0.008402</td>\n",
       "      <td>0.033026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>0.112667</td>\n",
       "      <td>0.003667</td>\n",
       "      <td>0.780000</td>\n",
       "      <td>0.779560</td>\n",
       "      <td>LinearSVC(C=1.0, class_weight=None, dual=True,...</td>\n",
       "      <td>1000</td>\n",
       "      <td>Isomap(eigen_solver='auto', max_iter=None, n_c...</td>\n",
       "      <td>3</td>\n",
       "      <td>{u'classify__C': 1000, u'reduce_dim': Isomap(e...</td>\n",
       "      <td>64</td>\n",
       "      <td>0.764706</td>\n",
       "      <td>0.808081</td>\n",
       "      <td>0.686275</td>\n",
       "      <td>0.707071</td>\n",
       "      <td>0.895833</td>\n",
       "      <td>0.823529</td>\n",
       "      <td>0.124022</td>\n",
       "      <td>4.713704e-04</td>\n",
       "      <td>0.085789</td>\n",
       "      <td>0.051644</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>0.025667</td>\n",
       "      <td>0.001000</td>\n",
       "      <td>0.820000</td>\n",
       "      <td>0.868390</td>\n",
       "      <td>LinearSVC(C=1.0, class_weight=None, dual=True,...</td>\n",
       "      <td>1000</td>\n",
       "      <td>TruncatedSVD(algorithm='randomized', n_compone...</td>\n",
       "      <td>2</td>\n",
       "      <td>{u'classify__C': 1000, u'reduce_dim': Truncate...</td>\n",
       "      <td>63</td>\n",
       "      <td>0.882353</td>\n",
       "      <td>0.909091</td>\n",
       "      <td>0.901961</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>0.696078</td>\n",
       "      <td>0.018625</td>\n",
       "      <td>1.123916e-07</td>\n",
       "      <td>0.105496</td>\n",
       "      <td>0.127370</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>0.020000</td>\n",
       "      <td>0.001000</td>\n",
       "      <td>0.966667</td>\n",
       "      <td>0.976827</td>\n",
       "      <td>LinearSVC(C=1.0, class_weight=None, dual=True,...</td>\n",
       "      <td>1000</td>\n",
       "      <td>TruncatedSVD(algorithm='randomized', n_compone...</td>\n",
       "      <td>3</td>\n",
       "      <td>{u'classify__C': 1000, u'reduce_dim': Truncate...</td>\n",
       "      <td>11</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.969697</td>\n",
       "      <td>0.921569</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.979167</td>\n",
       "      <td>0.960784</td>\n",
       "      <td>0.010677</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.033456</td>\n",
       "      <td>0.016785</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>64 rows × 20 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    mean_fit_time  mean_score_time  mean_test_score  mean_train_score  \\\n",
       "0        1.181333         0.002000         0.966667          0.963458   \n",
       "1        0.030000         0.001000         0.973333          0.983363   \n",
       "2        0.111333         0.003000         0.973333          0.976728   \n",
       "3        0.202000         0.002000         0.900000          0.913547   \n",
       "4        0.189000         0.009000         0.933333          0.943454   \n",
       "5        0.043333         0.011333         0.940000          0.950386   \n",
       "6        0.030000         0.001000         0.966667          0.966726   \n",
       "7        0.003333         0.000667         0.973333          0.983363   \n",
       "8        0.003333         0.001333         0.960000          0.973460   \n",
       "9        0.003667         0.000667         0.980000          0.973460   \n",
       "10       0.153667         0.002333         0.973333          0.966825   \n",
       "11       0.040000         0.003000         0.966667          0.953357   \n",
       "12       0.448667         0.004333         0.960000          0.960190   \n",
       "13       0.087333         0.004333         0.960000          0.956922   \n",
       "14       0.003667         0.001000         0.960000          0.973559   \n",
       "15       0.236333         0.001000         0.980000          0.973460   \n",
       "16       0.002667         0.000333         0.953333          0.980095   \n",
       "17       0.014333         0.005333         0.966667          0.989998   \n",
       "18       0.035667         0.002333         0.966667          0.976728   \n",
       "19       0.113667         0.002000         0.973333          0.976827   \n",
       "20       0.118667         0.007667         0.946667          0.973460   \n",
       "21       0.053667         0.004333         0.953333          0.970093   \n",
       "22       0.004000         0.000667         0.953333          0.980095   \n",
       "23       0.004667         0.000667         0.966667          0.989998   \n",
       "24       0.004000         0.001333         0.946667          0.986730   \n",
       "25       0.003333         0.001333         0.966667          0.993365   \n",
       "26       0.054667         0.001667         0.953333          0.983363   \n",
       "27       0.102333         0.001667         0.973333          0.976728   \n",
       "28       0.021000         0.005000         0.933333          0.970192   \n",
       "29       0.017667         0.004667         0.933333          0.983462   \n",
       "..            ...              ...              ...               ...   \n",
       "34       0.149000         0.002000         0.966667          0.970093   \n",
       "35       0.108667         0.001667         0.953333          0.963458   \n",
       "36       0.742667         0.003667         0.920000          0.930184   \n",
       "37       0.148000         0.003667         0.933333          0.933551   \n",
       "38       0.062000         0.000667         0.966667          0.976728   \n",
       "39       0.036000         0.000000         0.973333          0.973361   \n",
       "40       0.009667         0.001333         0.953333          0.966726   \n",
       "41       0.010667         0.000667         0.973333          0.976728   \n",
       "42       0.058667         0.002000         0.960000          0.976728   \n",
       "43       0.046333         0.013667         0.966667          0.980095   \n",
       "44       0.272000         0.004667         0.926667          0.936819   \n",
       "45       0.085667         0.004000         0.933333          0.943553   \n",
       "46       0.013333         0.000667         0.960000          0.966726   \n",
       "47       0.024333         0.000667         0.966667          0.963260   \n",
       "48       0.033333         0.001000         0.946667          0.956724   \n",
       "49       0.010667         0.001000         0.966667          0.973460   \n",
       "50       0.037333         0.003000         0.953333          0.969994   \n",
       "51       0.094667         0.002000         0.960000          0.976728   \n",
       "52       0.147333         0.003333         0.926667          0.890176   \n",
       "53       0.158333         0.004000         0.886667          0.893345   \n",
       "54       0.164000         0.001000         0.913333          0.916914   \n",
       "55       0.296000         0.000333         0.933333          0.950188   \n",
       "56       0.039667         0.000333         0.940000          0.956724   \n",
       "57       0.021667         0.000667         0.946667          0.946821   \n",
       "58       0.063000         0.002000         0.893333          0.936522   \n",
       "59       0.032667         0.004333         0.946667          0.966825   \n",
       "60       0.052000         0.003333         0.913333          0.889978   \n",
       "61       0.112667         0.003667         0.780000          0.779560   \n",
       "62       0.025667         0.001000         0.820000          0.868390   \n",
       "63       0.020000         0.001000         0.966667          0.976827   \n",
       "\n",
       "                                       param_classify param_classify__C  \\\n",
       "0   SVC(C=10, cache_size=200, class_weight=None, c...                 1   \n",
       "1   SVC(C=10, cache_size=200, class_weight=None, c...                 1   \n",
       "2   SVC(C=10, cache_size=200, class_weight=None, c...                 1   \n",
       "3   SVC(C=10, cache_size=200, class_weight=None, c...                 1   \n",
       "4   SVC(C=10, cache_size=200, class_weight=None, c...                 1   \n",
       "5   SVC(C=10, cache_size=200, class_weight=None, c...                 1   \n",
       "6   SVC(C=10, cache_size=200, class_weight=None, c...                 1   \n",
       "7   SVC(C=10, cache_size=200, class_weight=None, c...                 1   \n",
       "8   SVC(C=10, cache_size=200, class_weight=None, c...                10   \n",
       "9   SVC(C=10, cache_size=200, class_weight=None, c...                10   \n",
       "10  SVC(C=10, cache_size=200, class_weight=None, c...                10   \n",
       "11  SVC(C=10, cache_size=200, class_weight=None, c...                10   \n",
       "12  SVC(C=10, cache_size=200, class_weight=None, c...                10   \n",
       "13  SVC(C=10, cache_size=200, class_weight=None, c...                10   \n",
       "14  SVC(C=10, cache_size=200, class_weight=None, c...                10   \n",
       "15  SVC(C=10, cache_size=200, class_weight=None, c...                10   \n",
       "16  SVC(C=10, cache_size=200, class_weight=None, c...               100   \n",
       "17  SVC(C=10, cache_size=200, class_weight=None, c...               100   \n",
       "18  SVC(C=10, cache_size=200, class_weight=None, c...               100   \n",
       "19  SVC(C=10, cache_size=200, class_weight=None, c...               100   \n",
       "20  SVC(C=10, cache_size=200, class_weight=None, c...               100   \n",
       "21  SVC(C=10, cache_size=200, class_weight=None, c...               100   \n",
       "22  SVC(C=10, cache_size=200, class_weight=None, c...               100   \n",
       "23  SVC(C=10, cache_size=200, class_weight=None, c...               100   \n",
       "24  SVC(C=10, cache_size=200, class_weight=None, c...              1000   \n",
       "25  SVC(C=10, cache_size=200, class_weight=None, c...              1000   \n",
       "26  SVC(C=10, cache_size=200, class_weight=None, c...              1000   \n",
       "27  SVC(C=10, cache_size=200, class_weight=None, c...              1000   \n",
       "28  SVC(C=10, cache_size=200, class_weight=None, c...              1000   \n",
       "29  SVC(C=10, cache_size=200, class_weight=None, c...              1000   \n",
       "..                                                ...               ...   \n",
       "34  LinearSVC(C=1.0, class_weight=None, dual=True,...                 1   \n",
       "35  LinearSVC(C=1.0, class_weight=None, dual=True,...                 1   \n",
       "36  LinearSVC(C=1.0, class_weight=None, dual=True,...                 1   \n",
       "37  LinearSVC(C=1.0, class_weight=None, dual=True,...                 1   \n",
       "38  LinearSVC(C=1.0, class_weight=None, dual=True,...                 1   \n",
       "39  LinearSVC(C=1.0, class_weight=None, dual=True,...                 1   \n",
       "40  LinearSVC(C=1.0, class_weight=None, dual=True,...                10   \n",
       "41  LinearSVC(C=1.0, class_weight=None, dual=True,...                10   \n",
       "42  LinearSVC(C=1.0, class_weight=None, dual=True,...                10   \n",
       "43  LinearSVC(C=1.0, class_weight=None, dual=True,...                10   \n",
       "44  LinearSVC(C=1.0, class_weight=None, dual=True,...                10   \n",
       "45  LinearSVC(C=1.0, class_weight=None, dual=True,...                10   \n",
       "46  LinearSVC(C=1.0, class_weight=None, dual=True,...                10   \n",
       "47  LinearSVC(C=1.0, class_weight=None, dual=True,...                10   \n",
       "48  LinearSVC(C=1.0, class_weight=None, dual=True,...               100   \n",
       "49  LinearSVC(C=1.0, class_weight=None, dual=True,...               100   \n",
       "50  LinearSVC(C=1.0, class_weight=None, dual=True,...               100   \n",
       "51  LinearSVC(C=1.0, class_weight=None, dual=True,...               100   \n",
       "52  LinearSVC(C=1.0, class_weight=None, dual=True,...               100   \n",
       "53  LinearSVC(C=1.0, class_weight=None, dual=True,...               100   \n",
       "54  LinearSVC(C=1.0, class_weight=None, dual=True,...               100   \n",
       "55  LinearSVC(C=1.0, class_weight=None, dual=True,...               100   \n",
       "56  LinearSVC(C=1.0, class_weight=None, dual=True,...              1000   \n",
       "57  LinearSVC(C=1.0, class_weight=None, dual=True,...              1000   \n",
       "58  LinearSVC(C=1.0, class_weight=None, dual=True,...              1000   \n",
       "59  LinearSVC(C=1.0, class_weight=None, dual=True,...              1000   \n",
       "60  LinearSVC(C=1.0, class_weight=None, dual=True,...              1000   \n",
       "61  LinearSVC(C=1.0, class_weight=None, dual=True,...              1000   \n",
       "62  LinearSVC(C=1.0, class_weight=None, dual=True,...              1000   \n",
       "63  LinearSVC(C=1.0, class_weight=None, dual=True,...              1000   \n",
       "\n",
       "                                     param_reduce_dim  \\\n",
       "0   PCA(copy=True, iterated_power='auto', n_compon...   \n",
       "1   PCA(copy=True, iterated_power='auto', n_compon...   \n",
       "2   NMF(alpha=0.0, beta_loss='frobenius', init=Non...   \n",
       "3   NMF(alpha=0.0, beta_loss='frobenius', init=Non...   \n",
       "4   Isomap(eigen_solver='auto', max_iter=None, n_c...   \n",
       "5   Isomap(eigen_solver='auto', max_iter=None, n_c...   \n",
       "6   TruncatedSVD(algorithm='randomized', n_compone...   \n",
       "7   TruncatedSVD(algorithm='randomized', n_compone...   \n",
       "8   PCA(copy=True, iterated_power='auto', n_compon...   \n",
       "9   PCA(copy=True, iterated_power='auto', n_compon...   \n",
       "10  NMF(alpha=0.0, beta_loss='frobenius', init=Non...   \n",
       "11  NMF(alpha=0.0, beta_loss='frobenius', init=Non...   \n",
       "12  Isomap(eigen_solver='auto', max_iter=None, n_c...   \n",
       "13  Isomap(eigen_solver='auto', max_iter=None, n_c...   \n",
       "14  TruncatedSVD(algorithm='randomized', n_compone...   \n",
       "15  TruncatedSVD(algorithm='randomized', n_compone...   \n",
       "16  PCA(copy=True, iterated_power='auto', n_compon...   \n",
       "17  PCA(copy=True, iterated_power='auto', n_compon...   \n",
       "18  NMF(alpha=0.0, beta_loss='frobenius', init=Non...   \n",
       "19  NMF(alpha=0.0, beta_loss='frobenius', init=Non...   \n",
       "20  Isomap(eigen_solver='auto', max_iter=None, n_c...   \n",
       "21  Isomap(eigen_solver='auto', max_iter=None, n_c...   \n",
       "22  TruncatedSVD(algorithm='randomized', n_compone...   \n",
       "23  TruncatedSVD(algorithm='randomized', n_compone...   \n",
       "24  PCA(copy=True, iterated_power='auto', n_compon...   \n",
       "25  PCA(copy=True, iterated_power='auto', n_compon...   \n",
       "26  NMF(alpha=0.0, beta_loss='frobenius', init=Non...   \n",
       "27  NMF(alpha=0.0, beta_loss='frobenius', init=Non...   \n",
       "28  Isomap(eigen_solver='auto', max_iter=None, n_c...   \n",
       "29  Isomap(eigen_solver='auto', max_iter=None, n_c...   \n",
       "..                                                ...   \n",
       "34  NMF(alpha=0.0, beta_loss='frobenius', init=Non...   \n",
       "35  NMF(alpha=0.0, beta_loss='frobenius', init=Non...   \n",
       "36  Isomap(eigen_solver='auto', max_iter=None, n_c...   \n",
       "37  Isomap(eigen_solver='auto', max_iter=None, n_c...   \n",
       "38  TruncatedSVD(algorithm='randomized', n_compone...   \n",
       "39  TruncatedSVD(algorithm='randomized', n_compone...   \n",
       "40  PCA(copy=True, iterated_power='auto', n_compon...   \n",
       "41  PCA(copy=True, iterated_power='auto', n_compon...   \n",
       "42  NMF(alpha=0.0, beta_loss='frobenius', init=Non...   \n",
       "43  NMF(alpha=0.0, beta_loss='frobenius', init=Non...   \n",
       "44  Isomap(eigen_solver='auto', max_iter=None, n_c...   \n",
       "45  Isomap(eigen_solver='auto', max_iter=None, n_c...   \n",
       "46  TruncatedSVD(algorithm='randomized', n_compone...   \n",
       "47  TruncatedSVD(algorithm='randomized', n_compone...   \n",
       "48  PCA(copy=True, iterated_power='auto', n_compon...   \n",
       "49  PCA(copy=True, iterated_power='auto', n_compon...   \n",
       "50  NMF(alpha=0.0, beta_loss='frobenius', init=Non...   \n",
       "51  NMF(alpha=0.0, beta_loss='frobenius', init=Non...   \n",
       "52  Isomap(eigen_solver='auto', max_iter=None, n_c...   \n",
       "53  Isomap(eigen_solver='auto', max_iter=None, n_c...   \n",
       "54  TruncatedSVD(algorithm='randomized', n_compone...   \n",
       "55  TruncatedSVD(algorithm='randomized', n_compone...   \n",
       "56  PCA(copy=True, iterated_power='auto', n_compon...   \n",
       "57  PCA(copy=True, iterated_power='auto', n_compon...   \n",
       "58  NMF(alpha=0.0, beta_loss='frobenius', init=Non...   \n",
       "59  NMF(alpha=0.0, beta_loss='frobenius', init=Non...   \n",
       "60  Isomap(eigen_solver='auto', max_iter=None, n_c...   \n",
       "61  Isomap(eigen_solver='auto', max_iter=None, n_c...   \n",
       "62  TruncatedSVD(algorithm='randomized', n_compone...   \n",
       "63  TruncatedSVD(algorithm='randomized', n_compone...   \n",
       "\n",
       "   param_reduce_dim__n_components  \\\n",
       "0                               2   \n",
       "1                               3   \n",
       "2                               2   \n",
       "3                               3   \n",
       "4                               2   \n",
       "5                               3   \n",
       "6                               2   \n",
       "7                               3   \n",
       "8                               2   \n",
       "9                               3   \n",
       "10                              2   \n",
       "11                              3   \n",
       "12                              2   \n",
       "13                              3   \n",
       "14                              2   \n",
       "15                              3   \n",
       "16                              2   \n",
       "17                              3   \n",
       "18                              2   \n",
       "19                              3   \n",
       "20                              2   \n",
       "21                              3   \n",
       "22                              2   \n",
       "23                              3   \n",
       "24                              2   \n",
       "25                              3   \n",
       "26                              2   \n",
       "27                              3   \n",
       "28                              2   \n",
       "29                              3   \n",
       "..                            ...   \n",
       "34                              2   \n",
       "35                              3   \n",
       "36                              2   \n",
       "37                              3   \n",
       "38                              2   \n",
       "39                              3   \n",
       "40                              2   \n",
       "41                              3   \n",
       "42                              2   \n",
       "43                              3   \n",
       "44                              2   \n",
       "45                              3   \n",
       "46                              2   \n",
       "47                              3   \n",
       "48                              2   \n",
       "49                              3   \n",
       "50                              2   \n",
       "51                              3   \n",
       "52                              2   \n",
       "53                              3   \n",
       "54                              2   \n",
       "55                              3   \n",
       "56                              2   \n",
       "57                              3   \n",
       "58                              2   \n",
       "59                              3   \n",
       "60                              2   \n",
       "61                              3   \n",
       "62                              2   \n",
       "63                              3   \n",
       "\n",
       "                                               params  rank_test_score  \\\n",
       "0   {u'classify__C': 1, u'reduce_dim': PCA(copy=Tr...               11   \n",
       "1   {u'classify__C': 1, u'reduce_dim': PCA(copy=Tr...                3   \n",
       "2   {u'classify__C': 1, u'reduce_dim': NMF(alpha=0...                3   \n",
       "3   {u'classify__C': 1, u'reduce_dim': NMF(alpha=0...               60   \n",
       "4   {u'classify__C': 1, u'reduce_dim': Isomap(eige...               48   \n",
       "5   {u'classify__C': 1, u'reduce_dim': Isomap(eige...               45   \n",
       "6   {u'classify__C': 1, u'reduce_dim': TruncatedSV...               11   \n",
       "7   {u'classify__C': 1, u'reduce_dim': TruncatedSV...                3   \n",
       "8   {u'classify__C': 10, u'reduce_dim': PCA(copy=T...               25   \n",
       "9   {u'classify__C': 10, u'reduce_dim': PCA(copy=T...                1   \n",
       "10  {u'classify__C': 10, u'reduce_dim': NMF(alpha=...                3   \n",
       "11  {u'classify__C': 10, u'reduce_dim': NMF(alpha=...               11   \n",
       "12  {u'classify__C': 10, u'reduce_dim': Isomap(eig...               25   \n",
       "13  {u'classify__C': 10, u'reduce_dim': Isomap(eig...               25   \n",
       "14  {u'classify__C': 10, u'reduce_dim': TruncatedS...               25   \n",
       "15  {u'classify__C': 10, u'reduce_dim': TruncatedS...                1   \n",
       "16  {u'classify__C': 100, u'reduce_dim': PCA(copy=...               32   \n",
       "17  {u'classify__C': 100, u'reduce_dim': PCA(copy=...               11   \n",
       "18  {u'classify__C': 100, u'reduce_dim': NMF(alpha...               11   \n",
       "19  {u'classify__C': 100, u'reduce_dim': NMF(alpha...                3   \n",
       "20  {u'classify__C': 100, u'reduce_dim': Isomap(ei...               40   \n",
       "21  {u'classify__C': 100, u'reduce_dim': Isomap(ei...               32   \n",
       "22  {u'classify__C': 100, u'reduce_dim': Truncated...               32   \n",
       "23  {u'classify__C': 100, u'reduce_dim': Truncated...               11   \n",
       "24  {u'classify__C': 1000, u'reduce_dim': PCA(copy...               40   \n",
       "25  {u'classify__C': 1000, u'reduce_dim': PCA(copy...               11   \n",
       "26  {u'classify__C': 1000, u'reduce_dim': NMF(alph...               32   \n",
       "27  {u'classify__C': 1000, u'reduce_dim': NMF(alph...                3   \n",
       "28  {u'classify__C': 1000, u'reduce_dim': Isomap(e...               48   \n",
       "29  {u'classify__C': 1000, u'reduce_dim': Isomap(e...               48   \n",
       "..                                                ...              ...   \n",
       "34  {u'classify__C': 1, u'reduce_dim': NMF(alpha=0...               11   \n",
       "35  {u'classify__C': 1, u'reduce_dim': NMF(alpha=0...               32   \n",
       "36  {u'classify__C': 1, u'reduce_dim': Isomap(eige...               57   \n",
       "37  {u'classify__C': 1, u'reduce_dim': Isomap(eige...               48   \n",
       "38  {u'classify__C': 1, u'reduce_dim': TruncatedSV...               11   \n",
       "39  {u'classify__C': 1, u'reduce_dim': TruncatedSV...                3   \n",
       "40  {u'classify__C': 10, u'reduce_dim': PCA(copy=T...               32   \n",
       "41  {u'classify__C': 10, u'reduce_dim': PCA(copy=T...                3   \n",
       "42  {u'classify__C': 10, u'reduce_dim': NMF(alpha=...               25   \n",
       "43  {u'classify__C': 10, u'reduce_dim': NMF(alpha=...               11   \n",
       "44  {u'classify__C': 10, u'reduce_dim': Isomap(eig...               55   \n",
       "45  {u'classify__C': 10, u'reduce_dim': Isomap(eig...               48   \n",
       "46  {u'classify__C': 10, u'reduce_dim': TruncatedS...               25   \n",
       "47  {u'classify__C': 10, u'reduce_dim': TruncatedS...               11   \n",
       "48  {u'classify__C': 100, u'reduce_dim': PCA(copy=...               40   \n",
       "49  {u'classify__C': 100, u'reduce_dim': PCA(copy=...               11   \n",
       "50  {u'classify__C': 100, u'reduce_dim': NMF(alpha...               32   \n",
       "51  {u'classify__C': 100, u'reduce_dim': NMF(alpha...               25   \n",
       "52  {u'classify__C': 100, u'reduce_dim': Isomap(ei...               55   \n",
       "53  {u'classify__C': 100, u'reduce_dim': Isomap(ei...               62   \n",
       "54  {u'classify__C': 100, u'reduce_dim': Truncated...               58   \n",
       "55  {u'classify__C': 100, u'reduce_dim': Truncated...               48   \n",
       "56  {u'classify__C': 1000, u'reduce_dim': PCA(copy...               45   \n",
       "57  {u'classify__C': 1000, u'reduce_dim': PCA(copy...               40   \n",
       "58  {u'classify__C': 1000, u'reduce_dim': NMF(alph...               61   \n",
       "59  {u'classify__C': 1000, u'reduce_dim': NMF(alph...               40   \n",
       "60  {u'classify__C': 1000, u'reduce_dim': Isomap(e...               58   \n",
       "61  {u'classify__C': 1000, u'reduce_dim': Isomap(e...               64   \n",
       "62  {u'classify__C': 1000, u'reduce_dim': Truncate...               63   \n",
       "63  {u'classify__C': 1000, u'reduce_dim': Truncate...               11   \n",
       "\n",
       "    split0_test_score  split0_train_score  split1_test_score  \\\n",
       "0            0.980392            0.959596           0.941176   \n",
       "1            0.980392            0.969697           0.960784   \n",
       "2            1.000000            0.969697           0.941176   \n",
       "3            0.960784            0.888889           0.901961   \n",
       "4            0.941176            0.919192           0.921569   \n",
       "5            0.960784            0.949495           0.921569   \n",
       "6            0.980392            0.959596           0.941176   \n",
       "7            0.980392            0.969697           0.960784   \n",
       "8            0.980392            0.959596           0.921569   \n",
       "9            0.980392            0.959596           0.960784   \n",
       "10           1.000000            0.959596           0.941176   \n",
       "11           1.000000            0.939394           0.921569   \n",
       "12           0.980392            0.949495           0.921569   \n",
       "13           0.980392            0.949495           0.921569   \n",
       "14           0.980392            0.969697           0.921569   \n",
       "15           0.980392            0.959596           0.960784   \n",
       "16           0.980392            0.969697           0.901961   \n",
       "17           0.980392            0.979798           0.921569   \n",
       "18           1.000000            0.959596           0.921569   \n",
       "19           1.000000            0.979798           0.941176   \n",
       "20           0.960784            0.959596           0.901961   \n",
       "21           0.980392            0.959596           0.901961   \n",
       "22           0.980392            0.969697           0.901961   \n",
       "23           0.980392            0.979798           0.921569   \n",
       "24           0.960784            0.979798           0.901961   \n",
       "25           1.000000            0.989899           0.921569   \n",
       "26           0.980392            0.969697           0.901961   \n",
       "27           1.000000            0.959596           0.921569   \n",
       "28           0.960784            0.959596           0.862745   \n",
       "29           0.960784            0.979798           0.862745   \n",
       "..                ...                 ...                ...   \n",
       "34           1.000000            0.949495           0.901961   \n",
       "35           0.980392            0.949495           0.882353   \n",
       "36           0.901961            0.898990           0.901961   \n",
       "37           0.941176            0.909091           0.901961   \n",
       "38           1.000000            0.959596           0.901961   \n",
       "39           0.980392            0.969697           0.960784   \n",
       "40           0.960784            0.939394           0.921569   \n",
       "41           0.980392            0.959596           0.941176   \n",
       "42           0.980392            0.959596           0.921569   \n",
       "43           0.980392            0.969697           0.921569   \n",
       "44           0.921569            0.909091           0.901961   \n",
       "45           0.941176            0.929293           0.901961   \n",
       "46           0.980392            0.949495           0.921569   \n",
       "47           1.000000            0.919192           0.921569   \n",
       "48           0.941176            0.919192           0.921569   \n",
       "49           0.980392            0.959596           0.941176   \n",
       "50           0.980392            0.939394           0.901961   \n",
       "51           0.980392            0.959596           0.921569   \n",
       "52           0.921569            0.868687           0.921569   \n",
       "53           0.941176            0.929293           0.745098   \n",
       "54           0.980392            0.959596           0.843137   \n",
       "55           0.960784            0.939394           0.862745   \n",
       "56           0.960784            0.919192           0.882353   \n",
       "57           0.980392            0.929293           0.921569   \n",
       "58           0.823529            0.868687           0.901961   \n",
       "59           0.960784            0.949495           0.921569   \n",
       "60           0.901961            0.848485           0.921569   \n",
       "61           0.764706            0.808081           0.686275   \n",
       "62           0.882353            0.909091           0.901961   \n",
       "63           1.000000            0.969697           0.921569   \n",
       "\n",
       "    split1_train_score  split2_test_score  split2_train_score  std_fit_time  \\\n",
       "0             0.979798           0.979167            0.950980      0.834724   \n",
       "1             1.000000           0.979167            0.980392      0.019131   \n",
       "2             0.989899           0.979167            0.970588      0.024998   \n",
       "3             0.959596           0.833333            0.892157      0.073544   \n",
       "4             0.979798           0.937500            0.931373      0.082426   \n",
       "5             0.989899           0.937500            0.911765      0.005185   \n",
       "6             0.979798           0.979167            0.960784      0.033297   \n",
       "7             1.000000           0.979167            0.980392      0.000471   \n",
       "8             1.000000           0.979167            0.960784      0.001247   \n",
       "9             1.000000           1.000000            0.960784      0.001700   \n",
       "10            0.989899           0.979167            0.950980      0.082883   \n",
       "11            0.969697           0.979167            0.950980      0.016309   \n",
       "12            0.989899           0.979167            0.941176      0.387964   \n",
       "13            0.989899           0.979167            0.931373      0.103042   \n",
       "14            1.000000           0.979167            0.950980      0.000471   \n",
       "15            1.000000           1.000000            0.960784      0.298680   \n",
       "16            1.000000           0.979167            0.970588      0.000471   \n",
       "17            1.000000           1.000000            0.990196      0.016740   \n",
       "18            1.000000           0.979167            0.970588      0.017211   \n",
       "19            0.989899           0.979167            0.960784      0.075650   \n",
       "20            1.000000           0.979167            0.960784      0.118969   \n",
       "21            0.989899           0.979167            0.960784      0.019482   \n",
       "22            1.000000           0.979167            0.970588      0.000817   \n",
       "23            1.000000           1.000000            0.990196      0.000471   \n",
       "24            1.000000           0.979167            0.980392      0.001414   \n",
       "25            1.000000           0.979167            0.990196      0.001247   \n",
       "26            1.000000           0.979167            0.980392      0.010209   \n",
       "27            1.000000           1.000000            0.970588      0.037853   \n",
       "28            1.000000           0.979167            0.950980      0.006377   \n",
       "29            1.000000           0.979167            0.970588      0.010143   \n",
       "..                 ...                ...                 ...           ...   \n",
       "34            1.000000           1.000000            0.960784      0.082660   \n",
       "35            0.989899           1.000000            0.950980      0.061157   \n",
       "36            0.979798           0.958333            0.911765      0.377928   \n",
       "37            0.979798           0.958333            0.911765      0.015895   \n",
       "38            1.000000           1.000000            0.970588      0.069296   \n",
       "39            0.979798           0.979167            0.970588      0.017205   \n",
       "40            1.000000           0.979167            0.960784      0.000471   \n",
       "41            1.000000           1.000000            0.970588      0.002357   \n",
       "42            1.000000           0.979167            0.970588      0.014055   \n",
       "43            1.000000           1.000000            0.970588      0.016111   \n",
       "44            0.979798           0.958333            0.921569      0.120044   \n",
       "45            0.979798           0.958333            0.921569      0.044515   \n",
       "46            0.989899           0.979167            0.960784      0.000471   \n",
       "47            1.000000           0.979167            0.970588      0.016740   \n",
       "48            1.000000           0.979167            0.950980      0.031584   \n",
       "49            1.000000           0.979167            0.960784      0.000471   \n",
       "50            1.000000           0.979167            0.970588      0.002055   \n",
       "51            1.000000           0.979167            0.970588      0.033370   \n",
       "52            0.929293           0.937500            0.872549      0.092903   \n",
       "53            0.858586           0.979167            0.892157      0.059918   \n",
       "54            0.898990           0.916667            0.892157      0.073025   \n",
       "55            0.979798           0.979167            0.931373      0.122695   \n",
       "56            1.000000           0.979167            0.950980      0.027633   \n",
       "57            0.979798           0.937500            0.931373      0.009843   \n",
       "58            0.989899           0.958333            0.950980      0.004546   \n",
       "59            1.000000           0.958333            0.950980      0.000471   \n",
       "60            0.929293           0.916667            0.892157      0.040357   \n",
       "61            0.707071           0.895833            0.823529      0.124022   \n",
       "62            1.000000           0.666667            0.696078      0.018625   \n",
       "63            1.000000           0.979167            0.960784      0.010677   \n",
       "\n",
       "    std_score_time  std_test_score  std_train_score  \n",
       "0     1.123916e-07        0.018302         0.012078  \n",
       "1     1.123916e-07        0.009021         0.012548  \n",
       "2     0.000000e+00        0.024581         0.009320  \n",
       "3     0.000000e+00        0.051766         0.032589  \n",
       "4     4.320365e-03        0.008575         0.026176  \n",
       "5     7.586547e-03        0.016260         0.031904  \n",
       "6     8.164374e-04        0.018302         0.009256  \n",
       "7     4.714827e-04        0.009021         0.012548  \n",
       "8     4.713704e-04        0.027588         0.018773  \n",
       "9     4.714266e-04        0.015925         0.018773  \n",
       "10    4.714266e-04        0.024581         0.016691  \n",
       "11    1.414280e-03        0.033456         0.012485  \n",
       "12    4.714266e-04        0.027588         0.021280  \n",
       "13    4.713704e-04        0.027588         0.024464  \n",
       "14    1.123916e-07        0.027588         0.020198  \n",
       "15    1.123916e-07        0.015925         0.018773  \n",
       "16    4.714827e-04        0.036876         0.014080  \n",
       "17    6.128208e-03        0.033333         0.008249  \n",
       "18    1.247214e-03        0.033456         0.017057  \n",
       "19    1.123916e-07        0.024581         0.012070  \n",
       "20    5.906653e-03        0.032944         0.018773  \n",
       "21    4.713704e-04        0.036876         0.014013  \n",
       "22    4.713704e-04        0.036876         0.014080  \n",
       "23    4.713704e-04        0.033333         0.008249  \n",
       "24    4.714827e-04        0.032944         0.009386  \n",
       "25    1.247235e-03        0.033456         0.004693  \n",
       "26    4.714266e-04        0.036876         0.012548  \n",
       "27    4.714266e-04        0.037154         0.017057  \n",
       "28    8.163401e-04        0.051211         0.021369  \n",
       "29    4.714266e-04        0.051211         0.012284  \n",
       "..             ...             ...              ...  \n",
       "34    1.123916e-07        0.046442         0.021644  \n",
       "35    4.714266e-04        0.051564         0.018706  \n",
       "36    4.715951e-04        0.026296         0.035468  \n",
       "37    4.713704e-04        0.023570         0.032720  \n",
       "38    4.714266e-04        0.046442         0.017057  \n",
       "39    0.000000e+00        0.009021         0.004566  \n",
       "40    4.713704e-04        0.023989         0.025097  \n",
       "41    4.714266e-04        0.024415         0.017057  \n",
       "42    1.123916e-07        0.027588         0.017057  \n",
       "43    1.510706e-02        0.033333         0.014080  \n",
       "44    4.713704e-04        0.023179         0.030815  \n",
       "45    0.000000e+00        0.023570         0.025822  \n",
       "46    4.714266e-04        0.027588         0.017022  \n",
       "47    4.713704e-04        0.033456         0.033394  \n",
       "48    8.165347e-04        0.023715         0.033239  \n",
       "49    0.000000e+00        0.018302         0.018773  \n",
       "50    1.414111e-03        0.036876         0.024746  \n",
       "51    1.123916e-07        0.027588         0.017057  \n",
       "52    4.713704e-04        0.007432         0.027705  \n",
       "53    8.164374e-04        0.102774         0.028878  \n",
       "54    1.123916e-07        0.056638         0.030309  \n",
       "55    4.713704e-04        0.051211         0.021192  \n",
       "56    4.714827e-04        0.042043         0.033239  \n",
       "57    4.714266e-04        0.025055         0.023334  \n",
       "58    0.000000e+00        0.055082         0.050530  \n",
       "59    4.027679e-03        0.018041         0.023466  \n",
       "60    4.713704e-04        0.008402         0.033026  \n",
       "61    4.713704e-04        0.085789         0.051644  \n",
       "62    1.123916e-07        0.105496         0.127370  \n",
       "63    0.000000e+00        0.033456         0.016785  \n",
       "\n",
       "[64 rows x 20 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "results_df = pd.DataFrame(grid.cv_results_)\n",
    "results_df"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}
